Abstract
We have studied an electrochemical detection method for the stimulants in the forensic samples using electrochemiluminescence (ECL). In this context, amphetamine type stimulant (methamphetamine (MA)) has been studied as co-reactants in the [Ru(bpy)3]2+ (where bpy is 2,2’-bipyridine) ECL system. This approach is developed based on a glassy carbon electrode modified with [Ru(bpy)3]2+ /Nafion composite film. LoD, LoQ and linear working range for MA are studied currently. The ECL intensity was found to be concentrations over the range of 5 x 10-8 to 2.5 x 10-4mol/L. LoD for MA is 1.94 x 10-10 mol/L. The regression coefficient is 0.9931 for the experiment. Our approach was applied in different medium such as saliva and human serum to detect MA This technique is simple, rapid, selective and sensitive, and shows potential for the high throughput quantitation of MA. the results show that the present electrochemical approach seems to provide a sensitive detection of MA in forensic applications.
Original language | English |
---|---|
Article number | 115420D |
Journal | Proceedings of SPIE |
Volume | 11542 |
DOIs | |
Publication status | Published - 20 Sept 2020 |
Keywords
- electrochemiluminescence
- biological matrices
- drug detection
- toxicological detection
Fingerprint
Dive into the research topics of 'Electrochemiluminescence detection of methamphetamine in biological matrices'. Together they form a unique fingerprint.Datasets
-
Data for: "Electrochemiluminescence Detection of Methamphetamine in Biological Matrices"
Dokuzparmak, E. (Creator) & Dennany, L. (Creator), University of Strathclyde, 9 Oct 2020
DOI: 10.15129/eec64b3d-ba2d-4e25-896c-c7b613358792, https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11542.toc
Dataset
-
Video presentation for: "Electrochemiluminescence Detection of Methamphetamine in Biological Matrices"
Dokuzparmak, E. (Creator) & Dennany, L. (Creator), University of Strathclyde, 9 Oct 2020
DOI: 10.15129/b03fe23a-8105-460b-972d-4a0fc22c2a8a, https://doi.org/10.1117/12.2573548
Dataset